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UbiOps Technical Documentation

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Documentation
How-To's & Tutorials
Troubleshooting
API Explorer
CLI
Client Libraries
Release Notes

UbiOps Technical Documentation

Documentation
Documentation
- Deployments
  Deployments
- Pipelines
- Making requests & processing data
  Making requests & processing data
- Importing & Exporting
- Monitoring
  Monitoring
- Project & User Management
  Project & User Management
- Interfacing with UbiOps
  Interfacing with UbiOps
- Miscellaneous
  Miscellaneous
- Questions & Support
- Back to UbiOps.com
How-To's & Tutorials
How-To's & Tutorials
- Introduction
- How-to's
  How-to's
  - Use a Numpy array as output
  - Create a requirements.txt
  - Use an external pip server
  - Request a deployment using the Python CL
  - Handle files (blobs) as input
  - Handle files (blobs) as output
  - Embed credentials and secrets
  - Train a model on UbiOps
  - Set up CI/CD from Git
  - Read and write from S3 buckets
  - Use blobs for persistent file storage
  - Integrate UbiOps with low-code platforms
    
    Integrate UbiOps with low-code platforms
- Starter Tutorials
  Starter Tutorials
  - UI Starter Tutorials
    
    UI Starter Tutorials
    
    UI deployment Starter Tutorial
    
    UI pipeline Starter Tutorial
  - Client library Starter Tutorial
  - CLI Starter Tutorial
- Tutorials
  Tutorials
  - Deploying models built with popular DS libraries
    Deploying models built with popular DS libraries
    
    Deploying a Scikit-Learn model
    
    Deploying a TensorFlow model
    
    Deploying an XGBoost model
  - Integration examples with cloud provider tools
    Integration examples with cloud provider tools
    
    Azure Data Factory & UbiOps
    
    Azure Machine Learning
    
    Azure Functions trigger
    
    Google Cloud Functions trigger
  - Integration examples with other tools
    Integration examples with other tools
    
    MLflow integration
    
    Mendix integration
    
    GSheets RFM pipeline
    
    Streamlit integration
  - Working with pipelines
    Working with pipelines
    
    Pokemon Pipeline
    
    Creating a pipeline with R and Python deployments
  - R Tutorials
    R Tutorials
    
    Deploying an R XGboost model
    
    Deploying an R XGboost pipeline
    
    Creating a pipeline with R and Python deployments
  - UI tutorials
    UI tutorials
    
    Multiplying a number
    
    Load & run a pre-trained model
    
    Image recognition
    
    GPU deployment
    
    Customer segmentation
Troubleshooting
Troubleshooting
- Problems with building
  Problems with building
- Problems during requests
  Problems during requests
- Miscellaneous problems
  Miscellaneous problems
  - Using blobs to (temporarily) store files in between pipeline steps
API Explorer
CLI
CLI
- Installation Guide
- Get Started
- Documentation
  Documentation
Client Libraries
Client Libraries
- Python
  Python
- R
  R
  - Installation Guide
  - Getting Started
  - Documentation
    Documentation
    
    Blobs
    
    Deployment Requests
    
    Deployments
    
    Imports And Exports
    
    Monitoring
    
    Organizations
    
    Pipeline Requests
    
    Pipelines
    
    Projects
    
    Request Schedules
    
    Roles
    
    Service Users
    
    Status
    
    User
Release Notes
Release Notes

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